Extended filtration model for diesel particulate filter based on diesel particulate matter morphology characteristics

Abstract

This study proposes an extended filtration model for diesel particulate filter based on diesel particulate matter morphology characteristics. This model introduces the parameter of variable effective density to modify the filtration model and develops the global filtration correction coefficient ϑp to consider the changes of PM morphological parameters. The specific calculation formulas of these two parameters are given in the paper. The filtration model proposed in this paper is based on the theory of spherical particles packed bed. Results show that the prediction error of the extended model can be as low as 0.66%, the average prediction error is 1.17%, and the prediction accuracy is improved by 34.08% compared with the former model. Filtration efficiency growth coefficient Egro exhibits a bimodal distribution, and the PM in the two particle size ranges of 110–140 nm and greater than 500 nm is more sensitive to the micro-changes in parameters caused by PM deposition in the porous substrate. In addition, the filtration time interval has the greatest influence on the growth rate, especially for the small and medium particle sizes ranging between 166.5 and 294.3 nm.